lostsoul8282

We are shifting to an agentic workflow. My thesis is "Code at Inference Speed." My CTO's counter-argument is that reviewing code is harder than writing it.

His concern is simple: If AI increases code volume by 10x, human review becomes a fatal bottleneck. He predicts technical debt will explode because humans can’t mentally verify that much logic that quickly. My concern is as competitors,clients, etc are able to release code quickly then we need to be faster on our product - clients expectations are increasing.

How do handle this? I know one option is to slow down releases but is there any other approaches people are taking.

I’m working on a site(NextJS, FastAPI, Postgres is the stack). I’m facing a challenge where each user is asking for different reporting and we are shifting to doing more and more reports that are only slightly different.

I think it would be easier to just expose my API to some BI tool to let the users build their own dashboards(and perhaps share the main ones we made).

I realize this probably exists and have found a few(powerBI embedded, metabase, etc). I have no experience in this area so I’m interested in what you are using and your experience with it?

For example, NetZero, diversity, etc..

Many big companies make netZero pledges but it seems like startups could make the same pledge but I do not see it.

Hi HN!

In my previous life at tech at BigCo, I was always given data from providers(bloomberg, reuters, etc) and processed it using my models.

I was asked recently how do you trust data that may not be audited and is self reported? i.e. say a company reports the number of women in the company or enviromental metrics.

I feel this is a general problem for any self reported data. How would you handle it?